34 citations · 69 across the 5 of their papers we have counts for
9 papers
IB-GAN: A Unified Approach for Multivariate Time Series Classification under Class Imbalance
Grace Deng, Cuize Han, Tommaso Dreossi +2
Classification of large multivariate time series with strong class imbalance is an important task in real-world applications. Standard methods of class weights, oversampling, or pa…
Scenic: A Language for Scenario Specification and Data Generation
Daniel J. Fremont, Edward Kim, Tommaso Dreossi +4
We propose a new probabilistic programming language for the design and analysis of cyber-physical systems, especially those based on machine learning. Specifically, we consider the…
A Formalization of Robustness for Deep Neural Networks
Tommaso Dreossi, Shromona Ghosh, Alberto Sangiovanni-Vincentelli +1
Deep neural networks have been shown to lack robustness to small input perturbations. The process of generating the perturbations that expose the lack of robustness of neural netwo…
VERIFAI: A Toolkit for the Design and Analysis of Artificial Intelligence-Based Systems
Tommaso Dreossi, Daniel J. Fremont, Shromona Ghosh +4
We present VERIFAI, a software toolkit for the formal design and analysis of systems that include artificial intelligence (AI) and machine learning (ML) components. VERIFAI particu…
Scenic: A Language for Scenario Specification and Scene Generation
Daniel J. Fremont, Tommaso Dreossi, Shromona Ghosh +3
We propose a new probabilistic programming language for the design and analysis of perception systems, especially those based on machine learning. Specifically, we consider the pro…
Semantic Adversarial Deep Learning
Tommaso Dreossi, Somesh Jha, Sanjit A. Seshia
Fueled by massive amounts of data, models produced by machine-learning (ML) algorithms, especially deep neural networks, are being used in diverse domains where trustworthiness is…